Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition

• Κύριοι συγγραφείς: Yanai, Haruo (Συγγραφέας), Takeuchi, Kei (Συγγραφέας), Takane, Yoshio (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: New York, NY : Springer New York, 2011.
• Σειρά: Statistics for Social and Behavioral Sciences
• Θέματα: Statistics.; Statistics, general.; Statistics for Life Sciences, Medicine, Health Sciences.

Aside from distribution theory, projections and the singular value decomposition (SVD) are the two most important concepts for understanding the basic mechanism of multivariate analysis. The former underlies the least squares estimation in regression analysis, which is essentially a projection of on...

Πίνακας περιεχομένων:

• Fundamentals of Linear Algebra
• Projection Matrices
• Generalized Inverse Matrices
• Explicit Representations
• Singular Value Decomposition (SVD)
• Various Applications.